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Vaginal birth after a caesarean section: the development of a Western European population-based prediction model for
E N C Schoorel1, S M J van Kuijk, S Melman
1Department of Obstetrics and Gynaecology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Objective:
To develop and internally validate a model that predicts the outcome of an intended vaginal birth after caesarean (VBAC) for a Western European population that can be used to personalise counselling for deliveries at term.
Design:
Registration-based retrospective cohort study.
Setting:
Five university teaching hospitals, seven non-university teaching hospitals, and five non-university non-teaching hospitals in the Netherlands.
Population:
A cohort of 515 women with a history of one caesarean section and a viable singleton pregnancy, without a contraindication for intended VBAC, who delivered at term.
Methods:
Potential predictors for a vaginal delivery after caesarean section were chosen based on literature and expert opinions. We internally validated the prediction model using bootstrapping techniques.
Main Outcome Measures:
Predictors for VBAC. For model validation, the area under the receiver operating characteristic curve (AUC) for discriminative capacity and calibration-per-risk-quantile for accuracy were calculated.
Results:
A total of 371 out of 515 women had a VBAC (72%). Variables included in the model were: estimated fetal weight greater than the 90(th) percentile in the third trimester; previous non-progressive labour; previous vaginal delivery; induction of labour; pre-pregnancy body mass index; and ethnicity. The AUC was 71% (95% confidence interval, 95% CI = 69-73%), indicating a good discriminative ability. The calibration plot shows that the predicted probabilities are well calibrated, especially from 65% up, which accounts for 77% of the total study population.
Conclusion:
We developed an appropriate Western European population-based prediction model that is aimed to personalise counselling for term deliveries.
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